class_docstr: Update the node feature hv with MLP, BN and ReLU.
code: def __init__(self, mlp):
      super(ApplyNodeFunc, self).__init__()
      self.mlp = mlp
      self.bn = nn.BatchNorm1d(self.mlp.output_dim)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Linear, ReLU, Sequential, LeakyReLU, Tanh, ELU
  from dgl.nn.pytorch.conv import GINConv
  from dgl.nn.pytorch.glob import SumPooling, AvgPooling, MaxPooling
  from torch.nn import BatchNorm1d
  from .None import register_model
  from .base import BaseAutoModel, activate_func
  from copy import deepcopy
  from ....utils import get_logger
label_desc: Use image node_id 1 to create a new ApplyNodeFunc object from inherited base classes: nn with example: obj = ApplyNodeFunc(mlp)